By Beth Kindig
Publication Date: 2026-06-05 00:00:00
Three months ago, GPUs were all the rage, and the idea that CPUs could challenge GPUs when it comes to AI budgets was unfathomable. The shift in this perception is evident not only in management commentary, but also in CPU design companies and OEMs raising forecasts that are now 2X+ higher, as many of the largest players have stated they did not foresee the magnitude of the surge in CPU demand from agentic AI.
In just six months, AMD has issued a massive increase to its server CPU market forecast, nearly doubling its expected CAGR to 35%—estimating that the market will eclipse $120 billion by 2030. Arm made a similar announcement in March, projecting that the total addressable market (TAM) for data center CPUs will grow to over $100 billion by its fiscal year 2031 (roughly calendar year 2030). This would represent a more than 4X increase over its current TAM estimate of $24 billion, equating to a 33% CAGR.
An important shift is driving these forecasts as the AI market transitions away from chatbots, which saw a CPU-to-GPU ratio that was heavily weighted toward GPUs from 2023-2025. As we move into agentic AI, an Intel and Georgia Tech paper has stated that “tool-dominated agentic AI workloads are significantly bottle-necked” with CPUs consuming up to 88% of the end-to-end latency. The paper further concludes that “with better quality GPUs, the bottleneck can swiftly shift more towards CPUs.”
What Intel and Georgia Tech are referring to, is that to scale agentic…



/Nvidia%20logo%20on%20phone%20screen%20with%20stock%20chart%20by%20xalien%20via%20Shutterstock.jpg?resize=1600,1007&ssl=1)
